Digital Commons Network^™

Quantifying Atmospheric Turbulence Effects On Image Quality Using A Deconvolution Algorithm, Ahmad M. Almalki

Theses and Dissertations

Imaging through turbulence is affected by several factors including imaging system specifications, imaging system setup and more importantly the atmospheric turbulence as it is uncontrollable. One important parameter which is used to quantify the atmospheric turbulence severity is the atmospheric coherence diameter (��₀ ), known as Fried's parameter. This thesis explores ways to characterize the atmospheric turbulence effects on image quality using simulated and laboratory generated turbulence where ��₀ is estimated using a maximum a posteriori (MAP) estimator and frequency domain analysis algorithms. Furthermore, image quality metrics such as Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM) …

An Analytical Framework For Photonic Storage And Retrieval: Implications For Quantum Optical Networks, Billie V. Deluca

Theses and Dissertations

Quantum information and communication is the next revolution in information technology. However, communication through quantum networks will require the ability to transmit, store, and interact with photonic quantum bits (qubits). The focus of this dissertation is a theoretical description of a promising technology for storage of photonic states employing electromagnetically induced transparency (EIT). A general semiclassical model for EIT photonic storage will be developed, a key capability required for understanding the effect of storage that is independent of the photonic state being stored. This dissertation demonstrates the capability of this model to predict light pulses retrieved from EIT storage as …

Atmospheric Propagation Of Qubits: Laboratory Experiments To Field Demonstrations, Keith A. Wyman

Theses and Dissertations

Free-space quantum networks can enable global-scale quantum communication via satellite-based nodes and quantum ground transceivers. To enable building of robust global quantum networks, it is critical to learn how the state of the qubit is transformed while propagating through the atmosphere. With such an overarching goal, we built a laboratory based atmospheric turbulence simulator (ATS) to characterize the effects of atmospheric turbulence on an entangled pair of photons as a function of statistical quantities such as the Fried parameter or scintillation index for long-distance communication. Specifically, the changes in the statistical properties associated with a quantum source was investigated using …

Uncertainties In Retrieval Of Remote Sensing Reflectance From Ocean Color Satellite Observations, Eder I. Herrera Estrella

Dissertations, Theses, and Capstone Projects

Ocean Color radiometry uses remote sensing to interpret ocean dynamics by retrieving remote sensing reflectance (������) from satellite imagery at different scales and over different time periods. ������ spectrum characterizes the ocean color that we observe, and from which we can discern concentrations of chlorophyll, organic and inorganic particles, and carbon fluxes in the ocean and atmosphere. ������ is derived from the total radiance at the top of the atmosphere (TOA). However, it only represents up to ten percent of the total signal. Hence, the retrieval of ������ from the total radiance at TOA involves the application of atmospheric correction …

Qc-Odkla: Quantized And Communication-Censored Online Decentralized Kernel Learning Via Linearized Admm, Ping Xu, Yue Wang, Xiang Chen, Zhi Tian

Electrical and Computer Engineering Faculty Publications

This article focuses on online kernel learning over a decentralized network. Each agent in the network receives online streaming data and collaboratively learns a globally optimal nonlinear prediction function in the reproducing kernel Hilbert space (RKHS). To overcome the curse of dimensionality issue in traditional online kernel learning, we utilize random feature (RF) mapping to convert the nonparametric kernel learning problem into a fixed-length parametric one in the RF space. We then propose a novel learning framework, named online decentralized kernel learning via linearized ADMM (ODKLA), to efficiently solve the online decentralized kernel learning problem. To enhance communication efficiency, we …

Qc-Sane: Robust Control In Drl Using Quantile Critic With Spiking Actor And Normalized Ensemble, Surbhi Gupta, Gaurav Singal, Deepak Garg, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

Recently Introduced Deep Reinforcement Learning (DRL) Techniques in Discrete-Time Have Resulted in Significant Advances in Online Games, Robotics, and So On. Inspired from Recent Developments, We Have Proposed an Approach Referred to as Quantile Critic with Spiking Actor and Normalized Ensemble (QC-SANE) for Continuous Control Problems, Which Uses Quantile Loss to Train Critic and a Spiking Neural Network (NN) to Train an Ensemble of Actors. the NN Does an Internal Normalization using a Scaled Exponential Linear Unit (SELU) Activation Function and Ensures Robustness. the Empirical Study on Multijoint Dynamics with Contact (MuJoCo)-Based Environments Shows Improved Training and Test Results Than …

Exploring Topological Phonons In Different Length Scales: Microtubules And Acoustic Metamaterials, Ssu-Ying Chen

Dissertations

The topological concepts of electronic states have been extended to phononic systems, leading to the prediction of topological phonons in a variety of materials. These phonons play a crucial role in determining material properties such as thermal conductivity, thermoelectricity, superconductivity, and specific heat. The objective of this dissertation is to investigate the role of topological phonons at different length scales.

Firstly, the acoustic resonator properties of tubulin proteins, which form microtubules, will be explored The microtubule has been proposed as an analog of a topological phononic insulator due to its unique properties. One key characteristic of topological materials is the …

Boundary Integral Equation Methods For Superhydrophobic Flow And Integrated Photonics, Kosuke Sugita

Dissertations

This dissertation presents fast integral equation methods (FIEMs) for solving two important problems encountered in practical engineering applications.

The first problem involves the mixed boundary value problem in two-dimensional Stokes flow, which appears commonly in computational fluid mechanics. This problem is particularly relevant to the design of microfluidic devices, especially those involving superhydrophobic (SH) flows over surfaces made of composite solid materials with alternating solid portions, grooves, or air pockets, leading to enhanced slip.

The second problem addresses waveguide devices in two dimensions, governed by the Helmholtz equation with Dirichlet conditions imposed on the boundary. This problem serves as a …

On Explainability Of Neural Networks, Cem Benar

Dissertations

It is widely reported that deep neural networks outperform most competitors for a range of applications. The state-of-the-art neural networks have built-in inductive bias of architectural choices, regularizations, optimizer types, and initialization methods. Using inductive bias is intuitive to enhance the model approximation. Deep neural networks are mostly dense and heavily overparameterized. They tend to be biased towards low-rank solutions to reduce complexity and improve generalization performance, known as implicit regularization. The implicit regularization as observed in specific architectures and various real-world data sets suggests to overparameterize neural networks judiciously and learn compressed representations (lower rank approximation) with improved performance. …

An Animated Introduction To Digital Logic Design, John D. Carpinelli

Open and Affordable Textbooks

There is a newer edition of this textbook available here.

This book is designed for use in an introductory course on digital logic design, typically offered in computer engineering, electrical engineering, computer science, and other related programs. Such a course is usually offered at the sophomore level. This book makes extensive use of animation to illustrate the flow of data within a digital system and to step through some of the procedures used to design and optimize digital circuits.

All of the animations for this book can be found here: https://digitalcommons.njit.edu/dld-animations/

Mathematical Model Of An Industrial Robot Built On The Basis Of Linear Motion Mechatron Modules, Matyokubov Nurbek Rustamovich, Rakhimov Temurbek Omonboyevich

Chemical Technology, Control and Management

The use of Industry 4.0 technologies in modern production serves to increase production efficiency. Robots and robotic complexes with innovative intelligent control are widely used in industrial production. However, studying their mechanical part, linear motion mechatronic modules and control system is a complex object. The variety and complexity of control methods and operating modes negatively affects the operator's working time and production productivity. In such cases, it is necessary to improve control methods and develop technologies used in industry, including robots and robotic manipulators, which allow to perform short movements with high accuracy and speed. In the article, the mathematical …

The Morphology Analysis Of Soil In Remote Sensing Image Processing, Mirzayan Mirzaaxmedovich Kamilov, Mirzaakbar Xakkulmirzayevich Hudayberdiev, Bobomurod Mamitjonovich Tojiboev

Chemical Technology, Control and Management

This article analyzed various techniques used in satellite image processing to analyze soil morphology. Analysis of soil morphology using satellite imagery plays a crucial role in soil science research, Land Management, and environmental monitoring. It provides an economical and efficient means of studying large-scale soil variability, providing information on land sustainable use, resource management and soil conservation decisions.

Results Of The Study Of The Pumpkin Drying Process, Jasur Esirgapovich Safarov, Shahnoza Abduvakhitovna Sultanova, Andrey Svyatoslavovich Ponasenko, Gani Toshkhujaevich Dadaev

Chemical Technology, Control and Management

The article presents the results of the study of the pumpkin drying process, comparisons with different drying models are carried out. A mathematical model for numerical analysis has been developed. Pumpkin drying rates are calculated and various drying models are investigated. 5 different drying models were used to verify the accuracy of experimental data and search for the most suitable model. The experimental data obtained for the drying air temperature of 45 °C, 55 °C and 65 °C were applied to various drying models.

Use Of Neural Networks In Intelligent Measurement Tools, N.R Yusupbekov, Y.Sh. Avazov, Umidjon Ruziev Phd

Chemical Technology, Control and Management

The paper presents algorithms for processing the measurement signal with the possibilities of adaptation, learning and decision making. A comparative analysis of the methods of intellectual processing of measurement data is carried out. A model of a measuring instrument for determining the structure of a neural network has been developed. The problem of error reduction due to measurement noise filtering with the use of neural networks is considered. The structure of the neural network has been developed for intelligent processing of the measurement signal and ensuring the implementation of the functions of reconfiguration, calibration, self-diagnosis and self-control. A neural network …

Systematic Analysis Of Methods Of Control Of Dynamic Objects In Conditions Of Non-Measurable Disturbances, Mamirov Farkhodovich Uktam, Buronov Mamurjon Ugli Bunyod

Chemical Technology, Control and Management

The article presents a systematic analysis of control methods of dynamic objects under non-measurable disturbances. It is important to study all the factors affecting the control object in order to increase the efficiency of the control system. Due to the immeasurable nature of disturbances affecting control objects, it is shown that they cause negative effects and increase the complexity of control systems in this case. In the control of dynamic objects of this type, the possibilities of control by indirect measurement of disturbances or by estimation of object position and disturbances have been explored. The use cases, shortcomings and achievements …

Development Of The Computer Model Of The Waste Water Treatment Process Using Ion-Exchange Resins In The Matlab Program, Jaloliddin Abdurazzakovich Eshbobaev, Bakhodir Tajiddinovich Khamidov, Adham Tilovovich Norkobilov, Orifjon Sharipovich Kodirov

Chemical Technology, Control and Management

In this work, a mathematical model of industrial wastewater treatment technology was formed. First, wastewater treatment technologies were analyzed and the technology of ion-exchange resin treatment was selected. A water purification device using ion-exchange resins was made, and tested on the Kungrad soda plant and the results were obtained. According to these results, it was determined that the cleaning coefficient of the device is up to 98-99%. In this article, a mathematical model of a wastewater treatment device using ion-exchange resins was developed using the stoichiometric matrix method. After the mathematical model of the process was found, a graph of …

Algorithms For Synthesis Of Adaptive Control Systems Based On The Neural Network Approach, Jasur Sevinov, Oxunjon Boborayimov, Sh.M. Abdishukurov

Chemical Technology, Control and Management

Here are algorithms for the synthesis of adaptive control systems based on the neural network approach presented. The issues of choice of architectures of neural networks that produce parametric identification of the object regulation. Adaptative neural networks that reproduce the optimal parameters of implemented controllers, methods of forming training samples for their training are considered. The other question of using the theory of artificial neural networks for approximating the functional of the controller's tuning parameters are determined. Structures of synthesized neural networks of parametric identification of objects with self-alignment in an open loop ACS are proposed. Algorithms made it possible …

Synthesis And Evaluation Of Organic Additives For Copper Electroplating Of Interconnects, Yue-Hui Zhai, Yi-Xiao Peng, Yan Hong, Yuan-Ming Chen, Guo-Yun Zhou, Wei He, Peng-Ju Wang, Xian-Ming Chen, Chong Wang

Journal of Electrochemistry

Copper interconnects are essential to the functionality, performance, power efficiency, reliability, and fabrication yield of electronic devices. They are widely found in chips, packaging substrates and printed circuit boards, and are often produced by copper electroplating in an acidic aqueous solution. Organic additives play a decisive role in regulating copper deposition to fill microgrooves, and micro-vias to form fine lines and interlayer interconnects. Generally, an additive package consists of three components (brightener, suppressor, and leveler), which have a synergistic effect of super-filling on electroplating copper when the concentration ratio is appropriate. Many works of literature have discussed the mechanism of …

Effect Of Amine Additives On Thermal Runaway Inhibition Of Sic||Ncm811 Batteries, Bo-Wen Hou, Long He, Xu-Ning Feng, Wei-Feng Zhang, Li Wang, Xiang-Ming He

Journal of Electrochemistry

The high energy density of NCM batteries with high nickel content is a key advantage in replacing fossil fuels and promoting clean energy development, at the same time, is also a fundamental cause of serious safety hazards in batteries. Primary and secondary amines can lead to ring-opening polymerization of common ethylene carbonate electrolytes, resulting in an isolation layer between the cathode and the anode, and improving the thermal safety of the battery. In this work, the safety of batteries is considered both at the material level and at the cell level, based on the chemical reactions between amines and the …

Effects Of Traps On Photo-Induced Interfacial Charge Transfer Of Ag-Tio2: Photoelectrochemical, Electrochemical And Spectroscopic Characterizations, Zhi-Hao Liang, Jia-Zheng Wang, Dan Wang, Jian-Zhang Zhou, De-Yin Wu

Journal of Electrochemistry

In the field of metal-semiconductor composites based plasmon-mediated chemical reactions, a clear and in-depth understanding of charge transfer and recombination mechanisms is crucial for improving plasmonic photocatalytic efficiency. However, the plasmonic photocatalytic reactions at the solid-liquid interface of the electrochemical systems involve complex processes with multiple elementary steps, multiple time scales, and multiple controlling factors. Herein, the combination of photoelectrochemical and electrochemical as well as spectroscopic characterizations has been successfully used to study the effects of traps on the photo-induced interfacial charge transfer of silver-titanium dioxide (Ag-TiO₂). The results show that the increase of surface hydroxyl groups may …

Hierarchical Based Classifcation Method Based On Fusion Ofgaussian Map Descriptors Foralzheimer Diagnosis Using T1‑Weighted Magnetic Resonance Imaging, Nourhan Zayed, Shereen E. Morsy, Inas A. Yassine

Mechanical Engineering

Alzheimer’s disease (AD) is considered one of the most spouting elderly diseases. In 2015, AD is reported the US’s sixth cause of death. Substantially, non-invasive imaging is widely employed to provide biomarkers supporting AD screening, diagnosis, and progression. In this study, Gaussian descriptors-based features are proposed to be efcient new biomarkers using Magnetic Resonance Imaging (MRI) T1-weighted images to diferentiate between Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI), and Normal controls (NC). Several Gaussian map-based features are extracted such as Gaussian shape operator, Gaussian curvature, and mean curvature. The aforementioned features are then introduced to the Support Vector Machine (SVM). …

Performance Of Siso And Mimo Antenna Systems In Suburban And Urban Scenarios For V2i Communications At 5.9 Ghz And 28 Ghz, Oluwaseun Falade

Theses and Dissertations

As the need for Vehicle to Infrastructure (V2I) innovations increases, further research is needed to test the performance of antennas installed on vehicles in realistic scenarios including their radiation patterns and optimal location. This thesis considers realistic suburban and urban scenarios with SISO and MIMO antennas for V2I systems at 5.9 GHz and 28 GHz. The simulation is based on Ray tracing (RT) channel models to accurately model the effects of obstacles such as buildings and vehicles on the communication signals. Time-varying vehicular environments are simulated using a 3-D RT tool involving a vehicle and a base station. This research …

A Feasibility Study Of A Wearable Health Monitoring Device Powered By Thermoelectric Generators, Sarah Schneider

Masters Theses

Implementation of thermoelectric generators (TEGs) as a power source for embedded systems has increased with the push toward alternative and renewable energy sources. Thermoelectric generators produce electrical energy from thermal energy through the Seebeck effect. The Seebeck effect is a phenomenon seen when a temperature difference at a joint of two different metals generates a DC current and electromotive force [1]. This has made TEGs desirable for embedded system applications because it would allow for extended wireless operation. TEGs are based on solid-state technology which means they do not consist of any moving parts which reduces wear and tear with …

Distributed Optimization With Limited Communication In Networks With Adversaries, Iyanuoluwa Emiola

Electronic Theses and Dissertations, 2020-2023

We all hope for the best but sometimes, one must plan for ways of dealing with the worst-case scenarios, especially in a network with adversaries. This dissertation illustrates a detailed description of distributed optimization algorithms over a network of agents, in which some agents are adversarial. The model considered is such that adversarial agents act to subvert the objective of the network. The algorithms presented in this dissertation are solved via gradient-based distributed optimization algorithm and the effects of the adversarial agents on the convergence of the algorithm to the optimal solution are characterized. The analyses presented establish conditions under …

Theoretical Analysis Of Charge Conduction And Rectification In Self-Assembled-Monolayers In Molecular Junctions, Francis Adoah

Electronic Theses and Dissertations, 2020-2023

As electrical devices shrink to the atomic scale, it is expected that Moore's law will soon be obsolete for semiconductor devices. In 1974, Avriam and Ratner predicted that organic devices could replace semiconductor technology, leading to extensive research on molecular-based organic devices. This dissertation delves into the theoretical frameworks used to examine the transport in molecular junctions and aims to enhance our comprehension of charge transport and conduction properties. The studies presented in this thesis illustrates that a molecule's alteration by just a single atom can change it from an insulator to a conductor, and also that, by fine-tuning the …

Optimized Beam-Forming For Massive Mimo- Ofdm System, Nelly M. Shafik, Hazem H. El-Banna

Mansoura Engineering Journal

Massive Multiple-Input Multiple-Output (MIMO) wireless communication systems, achieved by large number of antennas, is the main secrete of Fifth Generation (5G) wireless communication networks powerful. In this paper, novel active antennas selection algorithm is proposed with resulted in efficient system performance with only half number of antenna elements. In order to gain optimum performance of massive MIMO wireless communication systems, it is vital to well analyze channel models which is glory indication for massive MIMO system characteristics. In this paper, MIMO system is simulated in bad frequency selective fading channel which is considered the most matching channel in case of …

Vertical Federated Learning Using Autoencoders With Applications In Electrocardiograms, Wesley William Chorney

Theses and Dissertations

Federated learning is a framework in machine learning that allows for training a model while maintaining data privacy. Moreover, it allows clients with their own data to collaborate in order to build a stronger, shared model. Federated learning is of particular interest to healthcare data, since it is of the utmost importance to respect patient privacy while still building useful diagnostic tools. However, healthcare data can be complicated — data format might differ across providers, leading to unexpected inputs and incompatibility between different providers. For example, electrocardiograms might differ in sampling rate or number of leads used, meaning that a …

Physical Layer Security With Unmanned Aerial Vehicles For Advanced Wireless Networks, Aly Sabri Abdalla

Theses and Dissertations

Unmanned aerial vehicles (UAVs) are emerging as enablers for supporting many applications and services, such as precision agriculture, search and rescue, temporary network deployment, coverage extension, and security. UAVs are being considered for integration into emerging wireless networks as aerial users, aerial relays (ARs), or aerial base stations (ABSs). This dissertation proposes employing UAVs to contribute to physical layer techniques that enhance the security performance of advanced wireless networks and services in terms of availability, resilience, and confidentiality. The focus is on securing terrestrial cellular communications against eavesdropping with a cellular-connected UAV that is dispatched as an AR or ABS. …

Modeling Of Signals And Spectra: 5g And Beyond, Xianzhen Yang

Dissertations and Theses

The collection of papers addresses various aspects of spectra and signals in RF wireless systems for 5G and beyond. The first paper focuses on the nonlinear effects of amplified dual-band OFDM signals, providing a spectrum model for intermodulation and cross-modulation. The second paper extends this analysis beyond bandwidth restrictions, enabling accurate prediction of amplified dual-band spectrum. The third paper emphasizes the significance of out-of-band intermodulation products and derives an analytical expression using third-order intercept points. The fourth paper presents a unified spectrum expression for OFDM, FBMC, and F-OFDM, facilitating comparative insights into these signals. The fifth paper explores second-order intermodulation …

A Method For Economic Expansion Planning Of Transmission Networks Using Heuristic Rules And Non-Linear Optimization Model, Maged Gamal Lotfy, Mahmoud Ali Farrag, Mohamed Shibl Albags, Ahmed Hamdy Khalil

Mansoura Engineering Journal

This paper presents a method for economic planning of transmission networks in an iterative manner. The method is capable of solving large scale networks where the most "worst" new lines are deleted iteratively using heuristic rules. In each iteration, a relatively small size non-linear mathematical Programming model is built to enhance the deletion process. The non-linear model is based on full AC load flow where only the reactive power injected from different available reactive power sources are controlled plus the reference bus voltage magnitude. The deletion process is stopped when the deleting of any line from the rest set of …